• 제목/요약/키워드: predictive

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Safety Critical 시스템의 센서 결함 허용을 위한 Kalman Hybrid Redundancy 개발 (Development of Kalman Hybrid Redundancy for Sensor Fault-Tolerant of Safety Critical System)

  • 김만호;이석;이경창
    • 제어로봇시스템학회논문지
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    • 제14권11호
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    • pp.1180-1188
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    • 2008
  • As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

A Novel Predictive Digital Controlled Sensorless PFC Converter under the Boundary Conduction Mode

  • Wang, Jizhe;Maruta, Hidenori;Matsunaga, Motoshi;Kurokawa, Fujio
    • Journal of Power Electronics
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    • 제17권1호
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    • pp.1-10
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    • 2017
  • This paper presents a novel predictive digital control method for boundary conduction mode PFC converters without the need for detecting the inductor current. In the proposed method, the inductor current is predicted by analytical equations instead of being detected by a sensing-resistor. The predicted zero-crossing point of the inductor current is determined by the values of the input voltage, output voltage and predicted inductor current. Importantly, the prediction of zero-crossing point is achieved in just a single switching cycle. Therefore, the errors in predictive calculation caused by parameter variations can be compensated. The prediction of the zero-crossing point with the proposed method has been shown to have good accuracy. The proposed method also shows high stability towards variations in both the inductance and output power. Experimental results demonstrate the effectiveness of the proposed predictive digital control method for PFC converters.

직류(直流) 전동기(電動機)를 위한 디지탈 P.I.D 예측(豫測) 보상(報償) 제어기(制御器) (P.I.D Predictive Controllers for The Various Types of D.C Drives)

  • 김윤호;윤병도;양원영;조용현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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    • pp.278-282
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    • 1989
  • A Digital P.I.D Predictive Controller is applied to the various types of D.C drives. The system with predictive controllers is compared to the system with conventional P.I.D controllers. The effect of the predictive control for the practical applications are investigated. The stability of the system with predictive controllers is also studied.

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A Collaborative and Predictive Localization Algorithm for Wireless Sensor Networks

  • Liu, Yuan;Chen, Junjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권7호
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    • pp.3480-3500
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    • 2017
  • Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.

불확실 로봇 매니퓰레이터의 견실 예측 제어기 설계 (Robust Predictive Control of Robot Manipulators with Uncertainties)

  • 김정관;한명철
    • 제어로봇시스템학회논문지
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    • 제10권1호
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    • pp.10-14
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    • 2004
  • We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

A Predictive Two-Group Multinormal Classification Rule Accounting for Model Uncertainty

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • 제26권4호
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    • pp.477-491
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    • 1997
  • A new predictive classification rule for assigning future cases into one of two multivariate normal population (with unknown normal mixture model) is considered. The development involves calculation of posterior probability of each possible normal-mixture model via a default Bayesian test criterion, called intrinsic Bayes factor, and suggests predictive distribution for future cases to be classified that accounts for model uncertainty by weighting the effect of each model by its posterior probabiliy. In this paper, our interest is focused on constructing the classification rule that takes care of uncertainty about the types of covariance matrices (homogeneity/heterogeneity) involved in the model. For the constructed rule, a Monte Carlo simulation study demonstrates routine application and notes benefits over traditional predictive calssification rule by Geisser (1982).

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가변속냉동시스템의 효율적인 과열도제어를 위한 예측제어기 설계 (Design of Predictive Controller for Effective Superheat Control of Variable Speed Refrigeration System)

  • 최정필;;정석권
    • 대한설비공학회:학술대회논문집
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    • 대한설비공학회 2008년도 하계학술발표대회 논문집
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    • pp.9-15
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    • 2008
  • In this paper, we suggest PI control with a predictive controller to progress both energy saving and coefficient of performance(COP) in a variable speed refrigeration system. The capacity and superheat are controlled simultaneously and independently by an inverter and an electronic expansion valve respectively for saving energy and improving COP in the system. The refrigeration system has long dead time in superheat inherently. The dead time makes the system difficult to achieve the satisfactory quick control response, especially superheat control response. In order to solve this problem, we designed a predictive controller based on PI control to progress superheat control performance. The control performance was investigated through some experiments to verify the effectiveness of the predictive controller.

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모델 예측 제어를 활용한 충돌 회피 (Collision Avoidance using Model Predictive Control)

  • 최재웅;서종상;이경수
    • 자동차안전학회지
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    • 제5권2호
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    • pp.32-38
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    • 2013
  • This paper presents collision avoidance using model predictive control algorithm. A model predictive control algorithm determines lateral tire force and yaw moment and steering angle input and differential braking input is determined from lateral tire force and yaw moment. A constraint for model predictive control is designed for obstacle avoidance. A objective function is designed to minimize lateral tire force and yaw moment input and to follow changed lane after collision avoidance. The performance of proposed algorithm has been investigated via computer simulation conducted to vehicle dynamic software CARSIM and Matlab/Simulink.

Robust Predictive Feedback Control for Constrained Systems

  • Giovanini, Leonardo;Grimble, Michael
    • International Journal of Control, Automation, and Systems
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    • 제2권4호
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    • pp.407-422
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    • 2004
  • A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

바닥난방을 위한 부하 예측식 펄스제어 방식의 적용성 연구 (Application Study of the Predictive Pulse Control for Floor Heating System)

  • 조성환;김성수;김용봉;나희형
    • 대한설비공학회:학술대회논문집
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    • 대한설비공학회 2007년도 동계학술발표대회 논문집
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    • pp.167-175
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    • 2007
  • A predictive pulse control strategy as a means of improving the energy efficiency of radiant floor heating systems is explored. Experiments at the apartment with floor heating system are conducted to assess and compare the energy performance of the predictive pulse control strategy with an existing conventional control strategy. The Results showed that new suggested PPCM( Predictive Pulse Control Method) was available to decrease the gap of $1{\sim}1.5^{\circ}C$ between maximum and minimum indoor temperature of each rooms. Therefore PPCM method was favor to radiant floor heating system which have a delay time of 10-20 minutes for heat transfer by floor layers.

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